Model-free adaptive sliding controller for automotive active suspensions

Automotive active suspensions are designed to provide better ride comfort and handling capability. Since the active suspension system has nonlinear and time-varying characteristics, it is difficult to establish an accurate dynamic model for designing a model-based controller. Here, an adaptive sliding controller with fuzzy compensation is proposed for an active suspension system. The functional approximation technique is employed to represent the unknown functions, which releases the model-based requirement of the sliding mode control. In addition, a fuzzy scheme with online learning ability is employed to compensate for the modeling error of the functional approximation with finite number of terms for reducing the implementation difficulty. The proposed controller is employed on a quarter-car active suspension system. The simulation and experimental results both show that the proposed controller suppresses the oscillation amplitude of the suspension system effectively.